Estrogenic Active Stilbene Derivatives as Anti-Cancer Agents: A DFT and QSAR Study

IEEE/ACM Trans Comput Biol Bioinform. 2019 Mar-Apr;16(2):560-568. doi: 10.1109/TCBB.2017.2779505. Epub 2017 Dec 4.

Abstract

Exploring different quantum chemical quantities for lead compounds is an ongoing approach in identifying crucial structural activity related features that are contributing into their biological activities. Herein, activity-related quantum chemical calculations were performed for the selected estrogenic stilbene derivatives using density functional theory (DFT) with B3LYP functional and 6-311++G** basis set. In addition, specific activity-related geometry-independent drug-like properties are discussed for these derivatives. To obtain the mathematical model that correlates the chemical descriptors with their measured estrogenic activities, the quantitative structure activity relationship (QSAR) is established using multiple linear regression (MLR) and support vector regression (SVR) methods. Satisfactory fit with a reasonable regression correlation coefficient (${\rm{R}}^{2}= 0.78$R2=0.78) between predicted and experimental $pEC_{50}$pEC50 values is observed using MLR method. The present study identifies the essential physicochemical descriptors that effectively contribute in the estrogenic activity. The applied approach provides helpful insight into the designing novel estrogenic agents with improved anticancer activities.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antineoplastic Agents* / chemistry
  • Antineoplastic Agents* / metabolism
  • Density Functional Theory
  • Drug Discovery
  • Estrogens* / chemistry
  • Estrogens* / metabolism
  • Models, Molecular
  • Quantitative Structure-Activity Relationship
  • Static Electricity
  • Stilbenes* / chemistry
  • Stilbenes* / metabolism

Substances

  • Antineoplastic Agents
  • Estrogens
  • Stilbenes